1. Field of the Invention
This invention relates to enterprise collaboration systems and more particularly to systems and methods for searching data that lacks a strict taxonomy and identifying people that match inexact search criteria.
2. Background of the Invention
Humans often organize themselves into cooperative groups and organizations such as companies, joint ventures, partnerships, trusts, project teams, human families, clubs, unions, societies, political parties, governments, charitable organizations, armies, and the like. Whether of a personal, professional, or political nature, each such organization involves contributors who are affiliated with the organization by birth, invitation, employment, voluntary involvement, etc. Moreover, contributors occupy various roles in the governance, management, operations, and administration of such organizations.
The roles and the contributors who occupy them interact with each other within the context of relationships. These relationships, whether formally defined as part of an established hierarchy or informally agreed upon based on a pattern of interactions, involve delegation of activities and tasks that are undertaken on behalf of the organization. The activities and tasks may be assigned to, or performed by, a contributor based on his or her role within an organization or their particular skill set or qualifications. People may be affiliated with an organization as members or as external contributors, and their designated role may reflect this status. For example, a member of a company may be a manager or an officer, while an external contributor may be an independent contractor or a consultant.
In each such organization, there is a need to organize and visualize the various contributors, roles, and relationships to ensure efficiency in the organization's operations and management. To this end, organizations typically create and use hierarchical organization charts and trees containing visual depictions. Organizations may also create and use various other types of depictions of themselves in the form of relationship diagrams, task descriptions, project plans, and other similar graphical and illustrative views.
Whether during a building process or phase or during subsequent use, such tools may require a user to locate one or more persons. This may require searching of large datasets, be they on the Internet or in enterprise-based files. Such locating may be complicated by the fact that many individuals have names that are intentionally spelled in unconventional ways. Furthermore, unlike content, names are used cross-culture and cross-language. Thus, diverse phonetic and spelling conventions are used. Nicknames are also used extensively. Such nicknames often bear no letter-based or logical match to the name of the person who the searcher is seeking. Typographical errors (be they introduced by the searcher or located within the dataset being searched) are also common.
People-targeted searches also present unique challenges in terms of identifying which matched names are most likely the ones of interest to the searcher. In some cases, the concept of credibility or popularity can be used, but often this is not available or not appropriate. Crowd sourcing techniques can be used to identify people that are frequently of interest to other searchers. However, this does not often work well because the user population is small. Also, in many cases, the searcher may not be looking for the most popular person, but rather the most knowledgeable person, a person in a specific role, etc.
In view of the foregoing, what is needed is a system and method facilitating rapid, computerized searching for and location of persons.